Measuring Affective Response. In particular, we mirror the concerns by [1]}; notably, that (1) emotion lexicons are limited in coverage and do not include all possible terms in a language, and that (2) as languages and, in particular, our perceptions of words in them are by nature entities of change that inherently possess socio-cultural variations, emotion scores for words are not immutable, neither longitudinally nor socio-culturally. As such, while we have attempted to mitigate for this limitation by (1) choosing the largest Chinese emotion lexicon annotated for words sourced from the domain of social media and (2) comparing our findings to that of previous smaller-scale in-person studies that use varying methods to measure emotion when possible—even as no “gold standard” measure of emotional response exists, physiological, behavioral, or otherwise [2]}—we encourage future work to further examine these phenomena in a greater variety of contexts. Further, our study does not make explicit causal claims around factors of music choice and user predisposition, i.e. what caused users to choose to listen to a specific song, or what their states of mind were prior to making this choice. While our work shows evidence of variations in affective responses correlated with musical, lyrical, demographic, and mental health factors, like the quasi-causal results estimating demographic effects on listener affective responses, we do not argue that these alone explain the entirety of the associated variations. In moving towards truly causal studies [3]}, we encourage further direct participatory work to further examine these observations in larger, more controlled, and even cross-cultural contexts.
